Analyst, AI ML and Cloud Security
GSK is hiring an Analyst, AI ML and Cloud Security in London, United Kingdom. Level rates it ; you can apply on GSK.
Level's read on this job
- Little AI ●○○○ is how Level rates this role: aI is not part of the work.
- Some of the work can be done remotely, according to the posting.
- The posting mentions MLflow, RAG and MLOps among its tools and skills.
- GSK has 824 other open roles on Level.
- Posted in the last few days.
AI in this role
Analyst, AI ML & Cloud Security
Why Us!
At GSK, we unite science, technology and talent to get ahead of disease together. We are a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together. We’re proud to be leading a healthcare revolution, and we’re looking for people who can help us deliver on our ambition
Job Purpose:
Support AI engineering delivery on the platform and data fabric workstreams. You configure AI platform environments, document data fabric build outputs, maintain CI/CD pipeline documentation, and develop the automation that keeps the builds moving and surfaces failures before they affect delivery.
About the team: AI ML and Cloud Security is the function through which GSK is transforming security itself. The team designs and builds the agentic framework, a multi-agent platform moving security services across the Chief Security Office from rule-based to AI-driven operation. It owns AI architecture and AI engineering end to end: the agent layer, LLM orchestration, the AI and ML platform, and the data fabric pipeline that CAS designs, builds and tests before a managed service vendor operates it. The team also governs AI tool security posture, advises on cloud security across the Azure and GCP estate, and is the front door between GSK's business units and R&D and the technical AI function. AI security standards set here are binding on every AI initiative in GSK. Seventeen roles across the UK, India and the US.
What makes this role different: An entry point into AI platform engineering for someone with a scripting and automation background who wants to build depth in AI infrastructure. You will support senior engineers rather than lead workstreams, and a real share of the job is documentation and test evidence that has to be right, because a managed service vendor will operate the data fabric from it without anyone from CAS present. Curiosity and precision matter more here than existing AI experience.
Key Responsibilities:
This role will provide you the opportunity to lead key activities to progress your career. These responsibilities include some of the following:
- Configure and maintain AI platform environments for development and test.
- Document data fabric build outputs and keep the build registry accurate.
- Maintain CI/CD pipeline documentation to the standard the vendor needs to operate the fabric once it transfers.
- Develop automation scripts for pipeline health monitoring so failures surface before they affect delivery.
- Build and execute test cases for platform and data fabric builds.
- Maintain build records so the platform estate stays traceable and auditable.
- Work to the architecture specifications provided and raise gaps rather than filling them informally.
- Support senior engineers across the platform and data fabric workstreams.
- Raise defects and blockers early with enough detail to be actionable.
- Build subject matter depth in AI platform engineering and data pipeline delivery.
Why You!
We are seeking professionals with the following required skills and qualifications to help us achieve our goals:
Basic Qualifications:
- Experienced in AI, platform or software engineering with a relevant technical degree — domain focus: AI Engineering (AI platform and data fabric workstreams)
- Configuring AI platform environments and supporting LLM, agent and RAG pipeline builds — environment setup, embedding and vector index jobs, and evaluation runs
- Building and running test cases for AI components — prompt-injection, output-validation and regression tests for non-deterministic behaviour
- Python automation for AI pipeline health — data quality, ingestion failures, model and API latency, token usage and cost — with automated alerting
- Documenting data fabric builds and CI/CD pipelines to vendor-handover standard and maintaining build records, working to architecture specifications and raising gaps rather than filling them informally.
Preferred Qualifications:
- You have debugged a failing vector index rebuild and can explain what you changed.
- Azure or GCP fundamentals certification (AZ-900, AI-900 or equivalent)
- Working knowledge of prompt-injection test patterns from the OWASP Top 10 for LLM Applications, enough to extend an existing test suite.
- Terraform and Helm for environment provisioning, with enough Git discipline to work in a shared repository.
- Exposure to MLOps tooling — MLflow, model registries or CI/CD for model deployment.
Ready to apply?
Ready to lead the future of secure AI and cloud technology? Join GSK and help us make a real difference in improving health worldwide. Apply today. We look forward to hearing from you. (Please take a personal copy of the Job Description, as this will not be available online post closure of the advert)
Closing Date: 6th November 2026
Working Pattern
This role is based in the United Kingdom and offers a hybrid working model, with 2/3 days a week onsite at our central London HQ.
#GSKcso
#AGTech
#LI-Hybrid
Skills
AI for Cybersecurity, AI Platforms, Application Security, CI/CD, Cloud Security, Computer Programming, Data Security, Google Cloud Platform (GCP), Identity Access Management (IAM), Information Systems, Infrastructure Security, Kubernetes, Microsoft Azure, ML Security, Operating Systems Security, PHP (Scripting Language), Scripting, Security Engineering, Security Technologies, Security Testing, Vector Databases, Vulnerability Management
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive.
We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.
Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at UKRecruitment.Adjustments@gsk.com where you can also request a call.
Please note should your enquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the Link where you will find answers to multiple questions we receive
Important notice to Employment businesses/ Agencies
GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK’s compliance to all federal and state US Transparency requirements. For more information, please visit the Centers for Medicare and Medicaid Services (CMS) website at https://openpaymentsdata.cms.gov/
How we rate this
Analyst, AI ML and Cloud Security at GSK rates 21 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- What are the limits of MLflow that you've run into, and how did you work around them?
Adapt your resume
- List these exact terms on your resume: RAG, ML Ops, and MLflow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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